A STUDY OF LEARNING SATISFACTION AMONG STUDENTS USING AGRI-MAP AND CHATGPT IN THE COURSE "COMPUTER AND INFORMATION TECHNOLOGY FOR AGRICULTURAL COMMUNICATION"

Abstract

This research aimed to evaluate the level of student satisfaction with learning management that integrates the use of Agri-Map and ChatGPT in the course "Computer and Information Technology for Agricultural Communication." The sample consisted of 24 undergraduate students enrolled in this course during the second semester of the 2024 academic year, Faculty of Animal Science and Agricultural Technology, Silpakorn University, Phetchaburi IT Campus. The sample was selected using purposive sampling. Data were collected using a questionnaire, which was validated for content by three experts, yielding an Index of Item-Objective Congruence (IOC) ranging from 0.67 to 1.00, and demonstrated high reliability with a Cronbach's alpha coefficient of 0.85.

The results indicated that students had a high overall level of satisfaction with learning using Agri-Map and ChatGPT (M = 4.26, SD = 0.44). When considering each aspect, the highest satisfaction was found in teaching methods (M = 4.35, SD = 0.48), followed by content (M = 4.33, SD = 0.47), assessment and evaluation (M = 4.24, SD = 0.43), overall impression (M = 4.19, SD = 0.40), and instructional media (M = 4.17, SD = 0.38). For specific items, the highest satisfaction was with the "appropriateness of the content presented" (M = 4.50, SD = 0.51) and "variety of classroom activities" (M = 4.50, SD = 0.44), while the "suitability of supporting documents" received the lowest satisfaction (M = 4.00, SD = 0.20). These findings suggest that integrating Agri-Map and ChatGPT has strong potential to enhance learning in the field of computer and information technology for agricultural communication. However, it is recommended that instructional media be further developed to be more engaging and responsive to learners’ needs, and that students be encouraged to utilize these technologies more effectively.